Skip to content

Commit

Permalink
Fix TensorFlow number_attr and type_attr_list (#291)
Browse files Browse the repository at this point in the history
  • Loading branch information
@lutzroeder
lutzroeder committed Jun 28, 2019
1 parent 6a10ecf commit 52cd6aa
Show file tree
Hide file tree
Showing 4 changed files with 76 additions and 16 deletions.
45 changes: 45 additions & 0 deletions src/tf-metadata.json
View file
Original file line number Diff line number Diff line change
Expand Up @@ -7982,6 +7982,7 @@
{
"description": "int; List of Rank 1 Tensors each containing the bucketized values for a single feature.",
"name": "buckets",
"numberAttr": "num_features",
"type": 3
}
],
Expand Down Expand Up @@ -8136,26 +8137,31 @@
{
"description": "An output list of Rank 1 tensors indicating possible split node ids for each feature. The length of the list is num_features, but each tensor has different size as each feature provides different possible nodes. See above for details like shapes and sizes.",
"name": "node_ids_list",
"numberAttr": "num_features",
"type": 3
},
{
"description": "An output list of Rank 1 tensors indicating the best gains for each feature to split for certain nodes. See above for details like shapes and sizes.",
"name": "gains_list",
"numberAttr": "num_features",
"type": 1
},
{
"description": "An output list of Rank 1 tensors indicating the bucket id to compare with (as a threshold) for split in each node. See above for details like shapes and sizes.",
"name": "thresholds_list",
"numberAttr": "num_features",
"type": 3
},
{
"description": "A list of Rank 2 tensors indicating the contribution of the left nodes when branching from parent nodes (given by the tensor element in the output node_ids_list) to the left direction by the given threshold for each feature. This value will be used to make the left node value by adding to the parent node value. Second dimension size is 1 for 1-dimensional logits, but would be larger for multi-class problems. See above for details like shapes and sizes.",
"name": "left_node_contribs_list",
"numberAttr": "num_features",
"type": 1
},
{
"description": "A list of Rank 2 tensors, with the same shape/conditions as left_node_contribs_list, but just that the value is for the right node.",
"name": "right_node_contribs_list",
"numberAttr": "num_features",
"type": 1
}
],
Expand Down Expand Up @@ -8417,6 +8423,7 @@
{
"description": "float; List of Rank 2 Tensors each containing the quantile summary\n(value, weight, min_rank, max_rank) of a single feature.",
"name": "summaries",
"numberAttr": "num_features",
"type": 1
}
],
Expand Down Expand Up @@ -8624,6 +8631,7 @@
{
"description": "float; List of Rank 1 Tensors each containing the bucket boundaries for a feature.",
"name": "bucket_boundaries",
"numberAttr": "num_features",
"type": 1
}
],
Expand Down Expand Up @@ -9214,16 +9222,19 @@
{
"description": "A list (length: top_paths) of indices matrices. Matrix j,\nsize `(total_decoded_outputs[j] x 2)`, has indices of a\n`SparseTensor<int64, 2>`. The rows store: [batch, time].",
"name": "decoded_indices",
"numberAttr": "top_paths",
"type": 9
},
{
"description": "A list (length: top_paths) of values vectors. Vector j,\nsize `(length total_decoded_outputs[j])`, has the values of a\n`SparseTensor<int64, 2>`. The vector stores the decoded classes for beam j.",
"name": "decoded_values",
"numberAttr": "top_paths",
"type": 9
},
{
"description": "A list (length: top_paths) of shape vector. Vector j,\nsize `(2)`, stores the shape of the decoded `SparseTensor[j]`.\nIts values are: `[batch_size, max_decoded_length[j]]`.",
"name": "decoded_shape",
"numberAttr": "top_paths",
"type": 9
},
{
Expand Down Expand Up @@ -10577,6 +10588,7 @@
{
"description": "The `N` int32 vectors representing the starting offset\nof input tensors within the concatenated output.",
"name": "offset",
"numberAttr": "N",
"type": 3
}
],
Expand Down Expand Up @@ -13312,10 +13324,12 @@
"outputs": [
{
"name": "weights",
"numberAttr": "num_params",
"typeAttr": "T"
},
{
"name": "biases",
"numberAttr": "num_params",
"typeAttr": "T"
}
],
Expand Down Expand Up @@ -13427,10 +13441,12 @@
"outputs": [
{
"name": "weights",
"numberAttr": "num_params_weights",
"typeAttr": "T"
},
{
"name": "biases",
"numberAttr": "num_params_biases",
"typeAttr": "T"
}
],
Expand Down Expand Up @@ -16426,6 +16442,7 @@
"outputs": [
{
"name": "outputs",
"numberAttr": "num_partitions",
"typeAttr": "T"
}
],
Expand Down Expand Up @@ -34681,6 +34698,7 @@
"outputs": [
{
"name": "sparse_indices",
"numberAttr": "Nsparse",
"type": 9
},
{
Expand All @@ -34689,6 +34707,7 @@
},
{
"name": "sparse_shapes",
"numberAttr": "Nsparse",
"type": 9
},
{
Expand Down Expand Up @@ -34874,6 +34893,7 @@
"outputs": [
{
"name": "context_sparse_indices",
"numberAttr": "Ncontext_sparse",
"type": 9
},
{
Expand All @@ -34882,6 +34902,7 @@
},
{
"name": "context_sparse_shapes",
"numberAttr": "Ncontext_sparse",
"type": 9
},
{
Expand All @@ -34890,6 +34911,7 @@
},
{
"name": "feature_list_sparse_indices",
"numberAttr": "Nfeature_list_sparse",
"type": 9
},
{
Expand All @@ -34898,6 +34920,7 @@
},
{
"name": "feature_list_sparse_shapes",
"numberAttr": "Nfeature_list_sparse",
"type": 9
},
{
Expand All @@ -34906,6 +34929,7 @@
},
{
"name": "feature_list_dense_lengths",
"numberAttr": "Nfeature_list_dense",
"type": 9
}
],
Expand Down Expand Up @@ -34996,6 +35020,7 @@
"outputs": [
{
"name": "sparse_indices",
"numberAttr": "num_sparse",
"type": 9
},
{
Expand All @@ -35004,6 +35029,7 @@
},
{
"name": "sparse_shapes",
"numberAttr": "num_sparse",
"type": 9
},
{
Expand Down Expand Up @@ -35188,6 +35214,7 @@
"outputs": [
{
"name": "context_sparse_indices",
"numberAttr": "Ncontext_sparse",
"type": 9
},
{
Expand All @@ -35196,6 +35223,7 @@
},
{
"name": "context_sparse_shapes",
"numberAttr": "Ncontext_sparse",
"type": 9
},
{
Expand All @@ -35204,6 +35232,7 @@
},
{
"name": "feature_list_sparse_indices",
"numberAttr": "Nfeature_list_sparse",
"type": 9
},
{
Expand All @@ -35212,6 +35241,7 @@
},
{
"name": "feature_list_sparse_shapes",
"numberAttr": "Nfeature_list_sparse",
"type": 9
},
{
Expand Down Expand Up @@ -42096,6 +42126,7 @@
{
"description": "The `nested_row_splits` tensors that define the row-partitioning for the\nreturned RaggedTensor.",
"name": "output_nested_splits",
"numberAttr": "OUTPUT_RAGGED_RANK",
"typeAttr": "Tsplits"
},
{
Expand Down Expand Up @@ -42240,6 +42271,7 @@
{
"description": "A list of one or more Tensors representing the splits of the output\n`RaggedTensor`.",
"name": "output_nested_splits",
"numberAttr": "output_ragged_rank",
"typeAttr": "Tsplits"
},
{
Expand Down Expand Up @@ -43950,6 +43982,7 @@
{
"description": "A TensorList of embedding activations containing one Tensor per\nembedding table in the model.",
"name": "outputs",
"numberAttr": "num_outputs",
"type": 1
}
],
Expand Down Expand Up @@ -54455,11 +54488,13 @@
{
"description": "a list of vectors where each value is the delta\nweights associated with a sparse feature group.",
"name": "out_delta_sparse_weights",
"numberAttr": "num_sparse_features",
"type": 1
},
{
"description": "a list of vectors where the values are the delta\nweights associated with a dense feature group.",
"name": "out_delta_dense_weights",
"numberAttr": "num_dense_features",
"type": 1
}
],
Expand Down Expand Up @@ -54598,11 +54633,13 @@
{
"description": "a list of vectors where each value is the delta\nweights associated with a sparse feature group.",
"name": "out_delta_sparse_weights",
"numberAttr": "num_sparse_features",
"type": 1
},
{
"description": "a list of vectors where the values are the delta\nweights associated with a dense feature group.",
"name": "out_delta_dense_weights",
"numberAttr": "num_dense_features",
"type": 1
}
],
Expand Down Expand Up @@ -55789,6 +55826,7 @@
"outputs": [
{
"name": "output",
"numberAttr": "N",
"typeAttr": "out_type"
}
],
Expand Down Expand Up @@ -61669,16 +61707,19 @@
"outputs": [
{
"name": "output_indices",
"numberAttr": "num_split",
"type": 9
},
{
"description": "A list of 1-D tensors represents the values of the output sparse\ntensors.",
"name": "output_values",
"numberAttr": "num_split",
"typeAttr": "T"
},
{
"description": "A list of 1-D tensors represents the shape of the output sparse\ntensors.",
"name": "output_shape",
"numberAttr": "num_split",
"type": 9
}
],
Expand Down Expand Up @@ -62108,6 +62149,7 @@
{
"description": "They are identically shaped tensors, whose shape matches that of `value`\nexcept along `split_dim`, where their sizes are\n`values.shape[split_dim] / num_split`.",
"name": "output",
"numberAttr": "num_split",
"typeAttr": "T"
}
],
Expand Down Expand Up @@ -62167,6 +62209,7 @@
{
"description": "Tensors whose shape matches that of `value`\nexcept along `split_dim`, where their sizes are\n`size_splits[i]`.",
"name": "output",
"numberAttr": "num_split",
"typeAttr": "T"
}
],
Expand Down Expand Up @@ -65380,6 +65423,7 @@
"outputs": [
{
"name": "outputs",
"numberAttr": "num_replicas",
"typeAttr": "T"
}
],
Expand Down Expand Up @@ -69662,6 +69706,7 @@
{
"description": "The list of tensors unpacked from `value`.",
"name": "output",
"numberAttr": "num",
"typeAttr": "T"
}
],
Expand Down
38 changes: 22 additions & 16 deletions src/tf.js
View file
Original file line number Diff line number Diff line change
Expand Up @@ -446,22 +446,24 @@ tf.Node = class {
inputCount = inputNumber.i;
}
}
var result = {};
result.name = input.name;
else if (input.typeListAttr) {
var inputTypeListAttr = node.attr[input.typeListAttr];
if (inputTypeListAttr && inputTypeListAttr.list && inputTypeListAttr.list.type) {
inputCount = inputTypeListAttr.list.type.length;
}
}
var inputConnections = inputs.slice(inputIndex, inputIndex + inputCount).map((id) => {
return new tf.Connection(id, null, initializers[id]);
});
this._inputs.push(new tf.Argument(input.name, inputConnections));
inputIndex += inputCount;
}
}
else {
this._inputs = this._inputs.concat(inputs.slice(inputIndex).map((input, index) => {
return new tf.Argument((inputIndex + index).toString(), [
new tf.Connection(input, null, initializers[input])
]);
}));
}
this._inputs = this._inputs.concat(inputs.slice(inputIndex).map((input, index) => {
return new tf.Argument((inputIndex + index).toString(), [
new tf.Connection(input, null, initializers[input])
]);
}));

this._outputs = [];
var outputIndex = 0;
Expand All @@ -475,20 +477,24 @@ tf.Node = class {
outputCount = outputNumber.i;
}
}
else if (output.typeListAttr) {
var outputTypeListAttr = node.attr[output.typeListAttr];
if (outputTypeListAttr && outputTypeListAttr.list && outputTypeListAttr.list.type) {
outputCount = outputTypeListAttr.list.type.length;
}
}
var outputConnections = outputs.slice(outputIndex, outputIndex + outputCount).map((id) => {
return new tf.Connection(id, null, null);
});
this._outputs.push(new tf.Argument(output.name, outputConnections));
outputIndex += outputCount;
}
}
else {
this._outputs = this._outputs.concat(outputs.slice(outputIndex).map((output, index) => {
return new tf.Argument((outputIndex + index).toString(), [
new tf.Connection(output, null, null)
]);
}));
}
this._outputs = this._outputs.concat(outputs.slice(outputIndex).map((output, index) => {
return new tf.Argument((outputIndex + index).toString(), [
new tf.Connection(output, null, null)
]);
}));

this._controlDependencies = node.controlDependencies;
}
Expand Down
Loading

0 comments on commit 52cd6aa

Please sign in to comment.